Connectome 2.0: Developing the next generation human MRI scanner for bridging studies of the micro-, meso- and macro-connectome

摘要 我们推出 Connectome 2.0，这是用于成像结构解剖学的下一代人体 MRI 扫描仪 跨越微观、介观和宏观尺度的连通性。这项工作建立在我们的专业知识之上 在设计第一台具有 300 mT/m 最大梯度强度 (Gmax) 的人体连接体 MRI 扫描仪时， 人类连接组计划 (HCP) 是人类系统有史以来取得的最高成就。 HCP 的目标是 利用扩散绘制体内健康成人大脑的宏观结构连接 纤维束造影术。虽然这个工具为我们理解宏观尺度做出了重要贡献 连接拓扑，过去七年使用扫描仪的经验告诉我们，专用 高梯度性能扫描仪还可以获得丰富的扩散测量结果，提供 对神经组织微观结构进行无与伦比的体内评估，例如神经组织的相对大小和堆积密度 细胞和轴突。然而，当前的 Connectome 仪器解析全方位的能力有限。 由于基本设计，探测大脑微观和介观结构所需的长度尺度 局限性、重要的技术要素以及与大的快速切换梯度的生物相互作用。 我们使用第一代 Connectome 扫描仪的经验以及对其局限性的认识激励我们 下一代人体连接组MRI扫描仪（Connectome 2.0）实现的多站点提案 对更广泛的细胞和轴突尺寸尺度、形态和互连的敏感性 整个大脑。 我们的目标是将我们最初的经验转化为构建一种独一无二的高转换率、超 高梯度强度 MRI 扫描仪，针对神经组织微观结构和神经的研究进行了优化 跨多个长度尺度的电路。为了最大限度地提高该活体显微镜的分辨率以进行研究 对于活体人脑，我们将把扩散分辨率极限推向前所未有的水平（1）近 将当前 Gmax 加倍至 500 mT/m，并将最大转换速率加倍至 600 T/m/s； (2) 突破极限 射频接收线圈和梯度表征，以实现最大灵敏度，并大大降低 使用实时涡流校正 dMRI 采集的伪影； (3) 开发新的脉冲序列 实现体内最高的扩散分辨率和空间分辨率； (4) 校准 通过对扩散的系统验证，从下一代仪器获得测量结果 高保真模型和离体脑组织的微观结构指标逐渐变得更精细。我们 设想创建能够满足 BRAIN 2025 成像要求的终极扩散 MRI 机器 跨尺度，从探测细胞异质性和可塑性所需的微观尺度，到 介观尺度，用于列举定义细胞和细胞的皮质结构和连接性的区别 骨髓结构边界，以改善宏观连接的估计。

SUMMARY We present Connectome 2.0, the next-generation human MRI scanner for imaging structural anatomy and connectivity spanning the microscopic, mesoscopic and macroscopic scales. This work builds upon our expertise in engineering the first human Connectome MRI scanner with 300 mT/m maximum gradient strength (Gmax), the highest ever achieved for a human system, for the Human Connectome Project (HCP). The goal of the HCP was to map the macroscopic structural connections of the in vivo healthy adult human brain using diffusion tractography. While this instrument has made important contributions to our understanding of macroscale connectional topology, our experience with the scanner over the last seven years has taught us that dedicated high-gradient performance scanners can also acquire a rich array of diffusion measurements that provide unparalleled in vivo assessment of neural tissue microstructure, such as the relative size and packing density of cells and axons. However, the current Connectome instrument is limited in its ability to resolve the full range of length scales needed to probe the microscopic and mesoscopic structure of the brain, due to basic design limitations, important technical elements, and biological interactions with the large rapidly switching gradients. Our experience with the first generation Connectome scanner and realization of its limitations motivates our multi-site proposal for the next generation human Connectome MRI scanner (Connectome 2.0) to achieve sensitivity to a broader range of cellular and axonal size scales, morphologies, and interconnections represented throughout the brain. Our goal here is to translate our initial experience into building a one-of-a-kind high-slew rate, ultra- high-gradient strength MRI scanner that is optimized for the study of neural tissue microstructure and neural circuits across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current Gmax to 500 mT/m and tripling the maximum slew rate to 600 T/m/s; (2) pushing the limits of the RF receive coils and gradient characterization to enable maximum sensitivity with greatly reduced artifacts using real-time eddy current corrected dMRI acquisitions; (3) developing new pulse sequences to achieve the highest diffusion- and spatial-resolution ever achieved in vivo; and (4) calibrating the measurements obtained from this next generation instrument through systematic validation of the diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales. We envision creating the ultimate diffusion MRI machine capable of addressing the BRAIN 2025 mandate to image across scales, from the microscopic scale needed to probe cellular heterogeneity and plasticity, to the mesoscopic scale for enumerating the distinctions in cortical structure and connectivity that define cyto- and myeloarchitechtonic boundaries, to improvements in estimates of macroscopic connectivity.